Evidence map›Paper›PMID 26370471›Full record

ReviewCurrent opinion in genetics & development2015

Genomic investigations of evolutionary dynamics and epistasis in microbial evolution experiments.

Elizabeth R Jerison, Michael M Desai

Abstract readReview
In one paragraph

Review in Current opinion in genetics & development, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed.

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  20. Emerging Priorities for Microbiome Research.Frontiers in microbiology · 2020
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Elizabeth R JerisonDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, United States; Department of Physics, Harvard University, Cambridge, MA 02138, United States; FAS Center for Systems Biology, Harvard University, Cambridge, MA 02138, United States.
Michael M DesaiDepartment of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, United States; Department of Physics, Harvard University, Cambridge, MA 02138, United States; FAS Center for Systems Biology, Harvard University, Cambridge, MA 02138, United States. Electronic address: mmdesai@fas.harvard.edu.

Funding

Microbial Adaptation and the Statistics of Epistasis and PleiotropyR01GM104239 · NIGMS · HARVARD UNIVERSITY · PI DESAI, MICHAEL M · 2013 to 2025
$4.5M
NIGMS NIH HHS GM104239NIGMS NIH HHS R01 GM104239
6 · The paper itself

Abstract

Microbial evolution experiments enable us to watch adaptation in real time, and to quantify the repeatability and predictability of evolution by comparing identical replicate populations. Further, we can resurrect ancestral types to examine changes over evolutionary time. Until recently, experimental evolution has been limited to measuring phenotypic changes, or to tracking a few genetic markers over time. However, recent advances in sequencing technology now make it possible to extensively sequence clones or whole-population samples from microbial evolution experiments. Here, we review recent work exploiting these techniques to understand the genomic basis of evolutionary change in experimental systems. We first focus on studies that analyze the dynamics of genome evolution in microbial systems. We then survey work that uses observations of sequence evolution to infer aspects of the underlying fitness landscape, concentrating on the epistatic interactions between mutations and the constraints these interactions impose on adaptation.

Indexed as

Biological EvolutionAdaptation, PhysiologicalEpistasis, GeneticEscherichia coliEvolution, MolecularGenetic FitnessGenome, BacterialHigh-Throughput Nucleotide SequencingModels, GeneticSaccharomyces cerevisiaeSelection, Genetic

Identifiers

PMID26370471
PMCPMC4710057

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.